TY - GEN
T1 - Decision-Driven Execution
T2 - 37th IEEE International Conference on Distributed Computing Systems, ICDCS 2017
AU - Abdelzaher, Tarek
AU - Amin, Md Tanvir A.
AU - Bar-Noy, Amotz
AU - Dron, William
AU - Govindan, Ramesh
AU - Hobbs, Reginald
AU - Hu, Shaohan
AU - Kim, Jung Eun
AU - Lee, Jongdeog
AU - Marcus, Kelvin
AU - Yao, Shuochao
AU - Zhao, Yiran
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/7/13
Y1 - 2017/7/13
N2 - This paper introduces a novel paradigm for resource management in distributed systems, called decision-driven execution. The paradigm is appropriate for mission-driven systems, where the goal is to enable faster, leaner, and more effective decision making. All resource consumption, in this paradigm, is tied to the needs of making decisions on alternative courses of action. A point of departure from traditional architectures lies in interfaces that allow applications to specify their underlying decision logic. This specification, in turn, allows the system to reason about most effective means to meet information needs of decisions, resulting in simultaneous optimization of decision accuracy, cost, and speed. The paper discusses the overall vision of decision-driven execution, outlining preliminary work and novel challenges.
AB - This paper introduces a novel paradigm for resource management in distributed systems, called decision-driven execution. The paradigm is appropriate for mission-driven systems, where the goal is to enable faster, leaner, and more effective decision making. All resource consumption, in this paradigm, is tied to the needs of making decisions on alternative courses of action. A point of departure from traditional architectures lies in interfaces that allow applications to specify their underlying decision logic. This specification, in turn, allows the system to reason about most effective means to meet information needs of decisions, resulting in simultaneous optimization of decision accuracy, cost, and speed. The paper discusses the overall vision of decision-driven execution, outlining preliminary work and novel challenges.
KW - Decision-driven Execution
KW - Distributed Computing Paradigms
KW - IoT
KW - Learning
KW - Sensor Networks
UR - http://www.scopus.com/inward/record.url?scp=85027258134&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85027258134&partnerID=8YFLogxK
U2 - 10.1109/ICDCS.2017.318
DO - 10.1109/ICDCS.2017.318
M3 - Conference contribution
AN - SCOPUS:85027258134
T3 - Proceedings - International Conference on Distributed Computing Systems
SP - 1825
EP - 1835
BT - Proceedings - IEEE 37th International Conference on Distributed Computing Systems, ICDCS 2017
A2 - Lee, Kisung
A2 - Liu, Ling
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 5 June 2017 through 8 June 2017
ER -